Course of Study

The Master’s of Science Course of Study

• Four courses in applied analytic methods (two core courses with labs and two analytics electives)
• Two foundational courses in population health sciences 
• Two courses in population health sciences research methods and study design
• Two professional development seminars 
• Two electives 
• A capstone project
• An applied practicum
• A course in academic integrity and responsible conduct of research

    Core Course Descriptions

    Please Note: Course instructors and descriptions are subject to change.

    Fall 2019 courses

    PHS 701 Applied Analytic Methods for Population Health Sciences I
    Instructors: Drs. Emily O'Brien and Brad Hammill 
    3 Hours

    Students will get an introduction to study design, descriptive statistics, and analysis of statistical models with one or two predictor variables. Topics include: principles of study design, basic study designs, descriptive statistics, sampling, contingency tables, one- and two-way analysis of variance, simple linear regression, and analysis of covariance. Both parametric and nonparametric techniques are also explored. Core concepts are taught through team-based case studies and analysis of research datasets taken from the population health sciences literature and demonstrated in concert with PHS 703 (Introduction to SAS Programming for Population Health Sciences). Computational exercises will primarily use the SAS Statistical Computing Platform. 

    PHS 703 Introduction to Statistical Programming for Population Health Sciences I
    Instructors: Dr. Theresa Coles and Jared Dean, SAS Institute
    1.5 hours, concurrent with PHS 701

    Students will be introduced to statistical software packages (e.g., SAS Software System, R Statistical Computing Platform) to provide an introduction to the core ideas of programming, including data preparation, input/output, debugging, and strategies for program design. Students will learn to write code to perform descriptive, statistical, and graphical analyses, and write maintainable code, to test for correctness, and to apply basic principles of reproducibility. Programming techniques and their applications will be closely connected with the methods and examples presented in the co-requisite applied analytic methods course PHS 701. This course assumes minimal programming knowledge. 

    PHS 705 Topics in Population Health Sciences I
    Instructors: Drs. Leah Zullig, Matt Dupre, and Laura Richman 
    3 Hours

    Students will gain foundational knowledge in the US healthcare system, population health sciences, and health and healthcare including an introduction to major diseases and disorders. Topics include: overall structure of the US healthcare system, insurance, Medicare, Medicaid, VA system, the ACA, mental health, health economics, and quality of care.

    PHS 707 Population Health Sciences Research Methods and Study Design I
    Instructors: Drs. Bryce Reeve and Heather King 
    3 Hours

    This is the first in a two-course sequence that gives students a strong foundation in population health research methods. The course introduces critical concepts in research methods, including varying types of validity, reliability, and causal inference. Topics include: sampling and interpretation of probability and nonprobability sampling ; an introduction to measurement theory; threats to internal validity; experimental designs; and quasi-experimental designs. 

    PHS 709 Professional Development I
    Instructors: Drs. Aaron McKethan and Asheley Skinner 
    1 hour

    This multi-semester course gives students a holistic view of their career choices and how to develop the tools they’ll need to succeed professionally. Fall semester focuses on creating a strong professional presence, proper networking techniques, American employer expectations, creating and maintaining a professional digital presence, and learning how to conduct and succeed at informational interviews . Students will attend interviewing and networking events with Duke staff and faculty as well as external guests. 
     

    Spring 2020 courses

    PHS 702 Applied Analytic Methods for Population Health Sciences II 
    Instructors: Drs. Matt Maciejewski and Valerie Smith 
    3 Hours

    This course is a continuation of PHS 701. Topics include: analysis of multivariable statistical models with continuous, dichotomous and survival outcomes. Topics include mixed effects models, generalized linear models (GLM), basic models for survival analysis and regression models for censored survival data, clustered data.  Students will explore parametric and nonparametric and perform computational exercises using the SAS System and R Statistical Computing Platform.

    PHS 704 Introduction to Statistical Programming for Population Health Sciences II
    Instructors: Dr. Theresa Coles and Jared Dean, SAS Institute
    1.5 hours, concurrent with PHS 702 

    Students will build on programming learned in PHS 703 using the SAS Software System and R Statistical Computing Platform. Students will perform descriptive, statistical, and graphical analyses, and write maintainable code, test code for correctness, and apply basic principles of reproducibility. Programming and assignments will be closely connected with the methods and examples presented in the co-requisite applied analytic methods course PHS 702. 

    PHS 706 Topics in Population Health Sciences II
    Instructors: Drs. Hayden Bosworth and Virginia Wang 
    3 Hours

    This course is a continuation of topics introduced in PHS 705 including: definition and measurement of population health; an overview of determinants of health including medical care, socioeconomic status, the physical environment and individual behavior, and their interactions; an overview of health services research, dissemination and implementation science, epidemiology, and measurement sciences. 

    PHS 708 Population Health Sciences Research Methods and Study Design II
    Instructors: Drs. Lesley Curtis and Sudha Raman 
    3 Hours

    This is the second in a two-course sequence that gives students a strong foundation in population health research methods. Topics include: qualitative and mixed methods, and advanced designs relevant to population health. The course applies foundational design information to methods unique to population health, including pragmatic trials, administrative claims data, and electronic medical record data. The course culminates in the development of a strong research question for a literature review, using the methods learned to critique research on a topic of the student’s choosing. 

    PHS 710 Professional Development II
    Instructors: Drs. Aaron McKethan and Asheley Skinner  
    1 hour

    This course is a continuation of PHS 709 and teaches project and team management. This course will give the student a holistic view of career choices and development and the tools they will need to succeed as professionals in the world of work.  

    Electives

    You can choose an elective offered through DPHS or a pre-approved course housed in other departments. For the analytics elective requirement, you also have the option to take PhD-level courses within Population Health Sciences, once the department begins offering PhD level courses. 

    PHS Electives

    Cost Effectiveness Analysis
    Instructor: TBD
    3 Hours

    Students will learn methods for designing, performing, and interpreting costs-effectiveness analysis. Topics include: cost measurement and data sources, methods of economic evaluation, decision modeling, measurement of  health care outcomes, patient utilities, and representation of uncertainty. Students will also explore methods of incorporating such analyses into health policy. 

    Introduction to Qualitative Research Methods
    Instructor: TBD 
    3 Hours

    Students will learn the design and analysis of qualitative descriptive research. Topics include: study designs, data collection methods, interviewing techniques, analytical approaches, ethical issues, and writing strategies. Students will develop research questions and question guides; practice conducting in-depth interviews, focus group discussions, and observations; and analyze and write up mock qualitative data. 

    Qualitative Research Design I
    Instructor: TBD  
    3 Hours

    During this two-semester course, students will get hands-on experience in developing, conducting, analyzing, and writing up qualitative research. In the first semester, students will learn various approaches to qualitative research, study designs, data collection methods, interviewing techniques, analytical approaches, and ethical issues. Working in groups, students will apply this information to design their own qualitative research study and prepare a study protocol for IRB submission. 

    Qualitative Research Design II
    Instructor: TBD  
    3 Hours

    The second semester of this course, students will conduct their IRB-approved qualitative research study, applying the qualitative inquiry skills learned in the first semester. Students will also learn and apply qualitative data management methods, conduct a rigorous analysis of their study data, and write up their findings. 

    Genetics and Genomics in Population Health Sciences
    Instructor: TBD  
    3 Hours

    Students will cover two topics in this course. The first is how ten years of research, using genome-wide association study (GWAS) methods and related techniques, has revolutionized the understanding of the human genome. The second is how this knowledge can be applied to improve public health, including applications related to understand etiology and identifying intervention targets, risk stratification, and population surveillance.

    Stated Preference Research
    Instructor: TBD  
    3 Hours

    Students will learn the conceptual framework that supports stated-preference research in contrast to patient-reported outcomes and health-state utility methods. At the course conclusion, students will be able to identify appropriate uses of different preference-elicitation formats, and will get experience in conducting and critically evaluating empirical preference research. 

    Stakeholder Engagement
    Instructor: TBD  
    3 Hours

    A shift towards patient-centered outcomes research (PCOR) has taken hold in clinical research. At its core, PCOR provides evidence to answer important clinical questions about healthcare services/practices and facilitate optimal patient and caregiver involvement. PCOR considers the patient’s lived experience and integrates patient preferences and values that address questions like: “Given my situation, will this treatment improve outcomes that are important to me like physical functioning and quality of life?”, “Given my values and preferences, which treatment choices (including no treatments) are best for me?” or “How will this treatment impact my family?” Stakeholders such as providers and policymakers are also concerned with what and how research is conducted—as it impacts their work. Thus, researchers have to view patients and other key stakeholders as respected collaborators in the research process. 

    This course provides a practical foundation in strategies and approaches to meaningfully engage patients, their caregivers, and other stakeholders in the research process. Topics include: identifying stallholder collaborators, methods for fostering meaningful engagement, how to support and train stakeholder collaborators, and building a stakeholder engagement into your research proposals. Instructor: 

    Social Disparities, Stress, and Health
    Instructor: TBD  
    3 Hours

    This course reviews theories and research that examines stress and the role it plays in social disparities in health. Students will learn basic concepts and models of stress as well as the mechanisms by which stress may influence health and explain social disparities.  Principles of Social and Behavioral Research Introduces methodology to explore fundamental concepts and theories useful in understanding social and behavioral determinants of health.  This course emphasizes quantitative research and social science methods applied to public health research.  Social Sciences & Population Health Students will be introduced to the theories and methods of social sciences in population health.  Through weekly seminars and lectures, this course covers: social epidemiological approaches to examining health disparities, behavioral science research methods, program planning & evaluation, ethnographic approaches, health communication, and community-based interventions.

    Population Health Economics
    Instructor: TBD  
    3 Hours

    Students will learn key concepts in health economics, focusing on understanding demand for health and health care, the role of health insurance, health care markets, health care financing, and features of supply, such as consolidation, competition and the role of ownership structure in supply and quality. Students will study why we treat health care markets differently than other markets in the economy, and the role of policy and government regulation to address market failure in health care. For example, students will look at what is information asymmetry and why does it need to be considered in health?. Students will also learn theories to understand how demand-side (patients) and supply-side (providers) incentives are intended to impact health behaviors and health care provision. 

    Improving Population Health-Policies and Programs
    Instructor: TBD  
    3 Hours

    This course examines policies and programs to address pressing and complex population health problems in the United States and abroad, such as obesity, end-of-life issues, and opioid abuse. Through case studies, students will assess current population health challenges and propose and assess innovative policy and programmatic solutions. The course emphasizes content knowledge of population health issues and policies, along with critical thinking, creativity and innovation, policy analysis skills, and written and verbal communication. 

    Cross-Listed Electives

    The following courses are offered by departments outside Population Health.  
     
    I. Health Services Research 
    A. CRP 248 - Clinical Trials 

    II. Implementation Science 
    A. CLP 213 - Health Care Organization and Policy 
    B. CLP 214 - Population Health Management Approaches 
    C. CLP 215 - Health Care Operations: Perspectives for Continuous Improvement 

    III. Comparative Effectiveness 
    A. CRP 262 - Systematic Reviews and Meta Analysis 
    B. CRP 266 - Concepts in Comparative Effectiveness Research 

    IV. Cost Effectiveness
    A. ECON 608D - Introduction to Econometrics 
    B. ECON 612 - Time Series Econometrics 
    C. ECON 613 - Applied Econometrics in Microeconomics 
    D. ECON 620 - Game Theory with Applications of Economics and other Social Sciences 
    E. ECON 703 - Econometrics I 
    F. ECON 707 - Econometrics II 
    G. ECON 756 - Health Economics: Supply 
    H. ECON 757 - Health Economics: Demand 
    I. GLHLTH 531 - Cost-Benefit Analysis for Health and Environmental Policy 

    V. Measurement Science 
    A. POLSCI 732 - Research Design and Qualitative Methods (M) 
    B. SOCIOL 699 - Qualitative Methods in Sociology 
    C. SOCIOL 720 - Survey Research Methods

    VI. Decision Science 
    A. CRP 259 - Decision Sciences in Clinical Research 
    B. MMCI 517 - Spreadsheet Modeling and Decision Analysis 
    C. MMCI 540 - Managerial Analysis 

    VII. Epidemiology 
    A. GLHLTH 635 - Critical Readings in Environmental Epidemiology 
    B. GLHLTH 708 - Advanced Methods in Epidemiology 
    C. GLHLTH 710 - Intermediate Epidemiology 
    D. SOCIOL 720 - Survey Research Methods 
    E. UPGEN 533 - Genetic Epidemiology 

    VIII. Statistics 
    A. POLSCI 733 - Advanced Regression 
    B. PSY 767 - Applied Correlation and Regression Analysis 
    C. PSY 768 - Applied Structural Equation Modeling 
    D. PSY 770 - Applied Multilevel Modeling 
    E. SOCIOL 726S - Advanced Methods of Demographic Analysis 
    F. STA 521L - Modern Regression and Predictive Modeling 
    G. STA 523L - Programming for Statistical Science 
    H. STA 601 - Bayesian and Modern Statistical Data Analysis
     
    IX. Data Science 
    A. COMPSCI 316 - Introduction to Database Systems 
    B. COMPSCI 516 - Database Systems 
    C. SOCIOL 728 - Advanced Methods: Introduction to Social Networks 
    D. COMPSCI 570 - Artificial Intelligence 
    E. COMPSCI 571D - Machine Learning 
    F. COMPSCI 579 - Statistical Data Mining
    G. MIDS 5XX - Data to Decision 
    H. MIDS 5XX - Data Marshaling & Management 
    I. MIDS 5XX - Data Visualization 
    J. MIDS 5XX - Data Science Seminar 
    K. MMCI 538 - Data, Information and Knowledge Representation 
    L. SOCIOL 728 - Advanced Methods: Introduction to Social Networks 
    M. STA 561D - Probabilistic Machine Learning 
    N. STA 571 - Advanced Probabilistic Machine Learning